A computing-in-memory macro based on three-dimensional resistive random-access memory

Qiang Huo, Yiming Yang, Yiming Wang, Dengyun Lei, Xiangqu Fu, Qirui Ren, Xiaoxin Xu, Qing Luo, Guozhong Xing, Chengying Chen, Xin Si, Hao Wu, Yiyang Yuan, Qiang Li, Xiaoran Li, Xinghua Wang*, Meng Fan Chang, Feng Zhang*, Ming Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

71 Citations (Scopus)

Abstract

Non-volatile computing-in-memory macros that are based on two-dimensional arrays of memristors are of use in the development of artificial intelligence edge devices. Scaling such systems to three-dimensional arrays could provide higher parallelism, capacity and density for the necessary vector–matrix multiplication operations. However, scaling to three dimensions is challenging due to manufacturing and device variability issues. Here we report a two-kilobit non-volatile computing-in-memory macro that is based on a three-dimensional vertical resistive random-access memory fabricated using a 55 nm complementary metal–oxide–semiconductor process. Our macro can perform 3D vector–matrix multiplication operations with an energy efficiency of 8.32 tera-operations per second per watt when the input, weight and output data are 8, 9 and 22 bits, respectively, and the bit density is 58.2 bit µm–2. We show that the macro offers more accurate brain MRI edge detection and improved inference accuracy on the CIFAR-10 dataset than conventional methods.

Original languageEnglish
Pages (from-to)469-477
Number of pages9
JournalNature Electronics
Volume5
Issue number7
DOIs
Publication statusPublished - Jul 2022

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Huo, Q., Yang, Y., Wang, Y., Lei, D., Fu, X., Ren, Q., Xu, X., Luo, Q., Xing, G., Chen, C., Si, X., Wu, H., Yuan, Y., Li, Q., Li, X., Wang, X., Chang, M. F., Zhang, F., & Liu, M. (2022). A computing-in-memory macro based on three-dimensional resistive random-access memory. Nature Electronics, 5(7), 469-477. https://doi.org/10.1038/s41928-022-00795-x